TY - GEN
T1 - Content Based Image Retrieval system using Wavelet Transformation and multiple input multiple task Deep Autoencoder
AU - Zhao, Xiangyuan
AU - Nutter, Brian
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/4/25
Y1 - 2016/4/25
N2 - In this paper, we propose an algorithm for a Content Based Image Retrieval (CBIR) system based on Wavelet Transformation and Deep Autoencoder (DAE). For the proposed algorithm, the image is first processed by wavelet transform and decomposed into wavelet coefficients. The wavelet coefficients then become the input for a multiple input multiple task deep autoencoder (MIMT-DAE). In our design, only the approximation coefficients (CA) and diagonal detail coefficients (CD) are used. The result of retrieval performance is tested on the MNIST handwriting data base. The testing results show that the combination of wavelet transformation and MIMT-DAE increases the performance of image retrieval for shape and texture compared to a traditional single input single task deep autoencoder with far fewer training parameters required.
AB - In this paper, we propose an algorithm for a Content Based Image Retrieval (CBIR) system based on Wavelet Transformation and Deep Autoencoder (DAE). For the proposed algorithm, the image is first processed by wavelet transform and decomposed into wavelet coefficients. The wavelet coefficients then become the input for a multiple input multiple task deep autoencoder (MIMT-DAE). In our design, only the approximation coefficients (CA) and diagonal detail coefficients (CD) are used. The result of retrieval performance is tested on the MNIST handwriting data base. The testing results show that the combination of wavelet transformation and MIMT-DAE increases the performance of image retrieval for shape and texture compared to a traditional single input single task deep autoencoder with far fewer training parameters required.
KW - CBIR
KW - Deep Neural Network
KW - Multiple Input Multiple Task Deep Autoencoder
KW - Wavelet Transformation
UR - http://www.scopus.com/inward/record.url?scp=84971349374&partnerID=8YFLogxK
U2 - 10.1109/SSIAI.2016.7459184
DO - 10.1109/SSIAI.2016.7459184
M3 - Conference contribution
AN - SCOPUS:84971349374
T3 - Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation
SP - 97
EP - 100
BT - 2016 IEEE Southwest Symposium on Image Analysis and Interpretation, SSIAI 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 6 March 2016 through 8 March 2016
ER -